org.deeplearning4j.optimize.api

Interface ConvexOptimizer

All Superinterfaces:

java.io.Serializable

All Known Implementing Classes:

BaseOptimizer, ConjugateGradient, LBFGS, LineGradientDescent, StochasticGradientDescent

public interface ConvexOptimizer
extends java.io.Serializable

Convex optimizer.

Method Summary

Modifier and Type	Method and Description
int	batchSize() The batch size for the optimizer
boolean	checkTerminalConditions(org.nd4j.linalg.api.ndarray.INDArray gradient, double oldScore, double score, int iteration) Check termination conditions setup a search state
ComputationGraphUpdater	getComputationGraphUpdater()
NeuralNetConfiguration	getConf()
Updater	getUpdater()
Pair<Gradient,java.lang.Double>	gradientAndScore() The gradient and score for this optimizer
boolean	optimize() Calls optimize
void	postStep(org.nd4j.linalg.api.ndarray.INDArray line) After the step has been made, do an action
void	preProcessLine() Pre preProcess a line before an iteration
double	score() The score for the optimizer so far
void	setBatchSize(int batchSize) Set the batch size for the optimizer
void	setListeners(java.util.Collection<IterationListener> listeners)
void	setUpdater(Updater updater)
void	setUpdaterComputationGraph(ComputationGraphUpdater updater)
void	setupSearchState(Pair<Gradient,java.lang.Double> pair) Based on the gradient and score setup a search state
void	updateGradientAccordingToParams(Gradient gradient, Model model, int batchSize) Update the gradient according to the configuration such as adagrad, momentum, and sparsity

Method Detail

score

double score()

The score for the optimizer so far

Returns:

the score for this optimizer so far

getUpdater

Updater getUpdater()

getComputationGraphUpdater

ComputationGraphUpdater getComputationGraphUpdater()

setUpdater

void setUpdater(Updater updater)

setUpdaterComputationGraph

void setUpdaterComputationGraph(ComputationGraphUpdater updater)

setListeners

void setListeners(java.util.Collection<IterationListener> listeners)

getConf

NeuralNetConfiguration getConf()

gradientAndScore

Pair<Gradient,java.lang.Double> gradientAndScore()

The gradient and score for this optimizer

Returns:

the gradient and score for this optimizer

optimize

boolean optimize()

Calls optimize

Returns:

whether the convex optimizer converted or not

batchSize

int batchSize()

The batch size for the optimizer

Returns:

setBatchSize

void setBatchSize(int batchSize)

Set the batch size for the optimizer

Parameters:

batchSize -

preProcessLine

void preProcessLine()

Pre preProcess a line before an iteration

postStep

void postStep(org.nd4j.linalg.api.ndarray.INDArray line)

After the step has been made, do an action

Parameters:

line -

setupSearchState

void setupSearchState(Pair<Gradient,java.lang.Double> pair)

Based on the gradient and score setup a search state

Parameters:

pair - the gradient and score

updateGradientAccordingToParams

void updateGradientAccordingToParams(Gradient gradient,
                                     Model model,
                                     int batchSize)

Update the gradient according to the configuration such as adagrad, momentum, and sparsity

Parameters:

gradient - the gradient to modify

model - the model with the parameters to update

batchSize - batchSize for update

checkTerminalConditions

boolean checkTerminalConditions(org.nd4j.linalg.api.ndarray.INDArray gradient,
                                double oldScore,
                                double score,
                                int iteration)

Check termination conditions setup a search state

Parameters:

gradient - layer gradients

iteration - what iteration the optimizer is on